Cineast: a multi-feature sketch-based video retrieval engine

Despite the tremendous importance and availability of large video collections, support for video retrieval is still rather limited and is mostly tailored to very concrete use cases and collections. In image retrieval, for instance, standard keyword search on the basis of manual annotations and content-based image retrieval, based on the similarity to query image(s), are well established search paradigms, both in academic prototypes and in commercial search engines. Recently, with the proliferation of sketch-enabled devices, alsosketch-based retrieval has received considerable attention. The latter two approaches are based on intrinsic image features and rely on the representation of the objects of a collection in the feature space. In this paper, we present Cineast, a multi-feature sketch-based video retrieval engine. The main objective of Cineast is to enable a smooth transition from content-based image retrieval to content-based video retrieval and to support powerful search paradigms in large video collections on the basis of user-provided sketches as query input. Cineast is capable of retrieving video sequences based on edge or color sketches as query input and even supports one or multiple exemplary video sequences as query input. Moreover, Cineast also supports a novel approach to sketch-based motion queries by allowing a user to specify the motion of objects within a video sequence by means of (partial) flow fields, also specified via sketches. Using an emergent combination of multiple different features, Cineast is able to universally retrieve video (sequences) without the need for prior knowledge or semantic understanding. The evaluation with a general purpose video collection has shown the effectiveness and the efficiency of the Cineast approach